Название: Python: A Practical Learning Approach
Автор: T.S. Murugesh, Shriram K. Vasudevan, Sini Raj Pulari
Издательство: CRC Press
Год: 2025
Страниц: 166
Язык: английский
Формат: pdf (true)
Размер: 31.2 MB

Python’s simplicity and versatility make it an ideal language for both beginners and experienced programmers. Its syntax facilitates a smooth learning curve, enabling individuals to concentrate on grasping programming concepts instead of wrestling with intricate syntax rules. The extensive standard library reinforces its practicality, offering pre-built modules and functions that reduce manual coding efforts. Python’s versatility is evident in its applications, spanning web development, data analysis, Machine Learning and automation. The language’s interactive nature supports real-time code experimentation, stepping up the learning process and enhancing understanding. Python’s wealth of online resources further enriches the learning experience, fostering a community where individuals can develop their programming skills. Python: A Practical Learning Approach exemplifies Python’s simplicity and versatility with numerous examples, ensuring a seamless learning journey. Beyond theory, the language’s practicality allows learners to actively apply their knowledge in real-world scenarios, establishing Python as an asset in education. Python can be used for building a variety of applications catering to different domains/sectors. One can build Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP), Data Analysis, Big Data, Automation, Embedded Applications and many other applications with Python. Therefore, it is an ideal choice for anyone to learn.

Название: The Lean-Agile Dilemma: Product Management Inside a Chunky Corporate
Автор: Katie Tamblin
Издательство: Apress
Год: 2024
Страниц: 259
Язык: английский
Формат: pdf (true), epub (true), mobi
Размер: 10.1 MB

Over the last decade, Lean-Agile principles have become the standard methodology by which product and technology teams operate. However, Lean-Agile was written for small companies seeking new markets to buy their innovative software products, not for an average corporation with a catalogue of existing software products that must be maintained and rebuilt. The typical tech-enabled business isn't a lean startup; it's a chunky corporate. This book offers an alternative software development methodology perfectly suited for chunky corporate product management. You’ll quickly find out how individual players in the corporate organization impact business performance. You’ll follow the story of Blake, a well-meaning but ultimately naive, CEO of a fictional company called Acme Tech. As he and Acme struggle to maintain business performance, it becomes apparent how embedded and complex his challenges are. Lean-Agile principles are regularly misapplied in the corporate environment, causing tension, missed deadlines, and inefficient working practices. You’ll see that managing software transformation at a large, mature business requires a new set of tools. Popular development methodologies are not well-suited for the replatforming exercises that chunky corporates inevitably face. This book helps product and technology leaders navigate software development projects at organizations grappling with the constraints of investor ownership.

Название: The Decision Maker's Handbook to Data Science: AI and Data Science for Non-Technical Executives, Managers, and Founders, 3rd Edition
Автор: Stylianos Kampakis
Издательство: Apress
Год: 2024
Страниц: 189
Язык: английский
Формат: pdf (true), epub (true), mobi
Размер: 10.1 MB

Data Science is expanding across industries at a rapid pace, and the companies first to adopt best practices will gain a significant advantage. To reap the benefits, decision makers need to have a confident understanding of data science and its application in their organization. This third edition delves into the latest advancements in AI, particularly focusing on large language models (LLMs), with clear distinctions made between AI and traditional data science, including AI's ability to emulate human decision-making. Artificial Intelligence (AI) is an umbrella term that captures an extraordinary field of computer science dedicated to creating systems capable of tasks that, until recently, required human intelligence. Today, AI stands at the forefront of innovation. The development of advanced algorithms and the exponential increase in computational power have catapulted AI from academic papers to real-world applications. Machine Learning (ML), a cornerstone of contemporary AI, is predicated on the principle that systems can learn from data, identify patterns, and make decisions with minimal human intervention. This paradigm shift from explicit programming to data-driven learning has been pivotal to AI’s success. By using algorithms that iteratively learn from data, ML has enabled AI to develop predictive models that are integral to a myriad of applications, from email filtering to sophisticated diagnostics in healthcare. Deep Learning, a subset of ML, has taken inspiration from the information processing patterns found in the human brain. It utilizes algorithms called neural networks which consist of layered structures resembling neurons. These networks can learn and make intelligent decisions on their own. Deep Learning has been fundamental in advancing AI, enabling machines to recognize images, decipher spoken words, and even generate human-like text.

Название: Coding Games in Scratch
Автор: Jon Woodcock
Издательство: DK
Год: 2024
Страниц: 226
Язык: английский
Формат: epub (true)
Размер: 21.1 MB

If you like playing computer games, why not make your own? This book has all you need to build amazing games, including thrilling racing challenges, zany platform games, and fiendish puzzles. Follow the simple steps to become an expert coder, using the popular programming language Scratch 3.0. This updated edition is the first to be tablet-computer friendly, making it even easier to get coding. Improve your coding skills and create your own games, before remixing and customizing them. Jumpy Monkey will show you how to simulate gravity in your games, or give Dog's Dinner a try to learn about collision detection. Pick up the fundamentals of computer programming in steps that make even the most difficult coding concepts fun and easy to understand. Don't just learn how computer code works—understand why it's done that way. Then share your games online and challenge friends and family to beat each other's scores. Once you've whizzed through the book, the possibilities are endless!

Название: Explainable, Interpretable, and Transparent AI Systems
Автор: B.K. Tripathy, Hari Seetha
Издательство: CRC Press
Год: 2025
Страниц: 355
Язык: английский
Формат: pdf (true)
Размер: 29.6 MB

Transparent Artificial Intelligence Systems facilitate understanding the decision-making process and provide opportunities in various aspects of providing explainability of AI models. This book provides up-to-date information on latest advancements in the field of Explainable AI, which is the critical requirement of AI/ML/DL models. It provides examples, case studies, latest techniques, and applications from the domains of health care, finance, network security etc. It also covers open-source interpretable tool kits such that practitioners can use them in their domains. There is an imminent need for explainable AI (XAI) techniques that are accountable, fair, transparent, and trustworthy without compromising the performance of the models, which would lead to better interaction with machines by users. It becomes essential to explain why and how decisions are made by machines. Machine Learning models must have the ability to provide reasoning, describe their merits and demerits, and convey an understanding of how they will behave. To achieve this, new or modified machine‑learning techniques that provide the required explanations must be developed. These models, in combination with human‑computer interface techniques, must be able to provide users with a greater understanding of why, how, and when a machine model or a deep learning model will perform well. It is important for any business to understand the process used to make decisions by AI models. Transparent AI systems facilitate understanding of the decision‑making process and also provide opportunities in various aspects of explaining AI models. Under the above background, this book aims to provide readers with up‑to‑date information on the latest advancements in the field of explainable AI, which is a critical requirement of AI, Machine Learning (ML), or Deep Learning (DL) models.

Название: Java and Algorithmic Thinking for the Complete Beginner Third Edition
Автор: Aristides S. Bouras
Издательство: Independently published
Год: 2024
Страниц: 694
Язык: английский
Формат: epub (true), mobi
Размер: 10.8 MB

Dive into the world of Java and algorithmic thinking with this book. This comprehensive guide for beginners covers everything from basic computer operations to advanced programming concepts. Begin your programming journey with a comprehensive course designed to introduce you to the world of Java and algorithmic thinking. The course starts by laying a solid foundation with an understanding of how computers work and an introduction to integrated development environments. As you advance, you'll delve into essential Java concepts, learning about variables, constants, and basic algorithmic concepts that are crucial for any aspiring programmer. Moving forward, the course offers a deep dive into more complex topics, including handling input and output, using operators, and creating trace tables. You'll get hands-on experience with Visual Studio Code and explore sequence control structures, manipulating numbers, and crafting complex mathematical expressions. In the final stages, the course covers advanced topics such as data structures, subprograms, and object-oriented programming. You'll learn to manipulate one-dimensional and two-dimensional arrays, work with HashMaps, and understand the intricacies of user-defined subprograms. The course concludes with a focus on file management and offers numerous tips and tricks to enhance your programming efficiency. By the end, you'll have a strong foundation in Java programming and algorithmic thinking, well-prepared to tackle more advanced challenges.

Название: LangChainJS For Beginners: A Beginner's Guide to AI Application Development With LangChain, jаvascript, OpenAI/ChatGPT, Google/Gemini and Other LLMs
Автор: Nathan Sebhastian
Издательство: Independently published
Год: 2024
Страниц: 189
Язык: английский
Формат: epub
Размер: 10.1 MB

LangChain supports both Python and jаvascript. This book focuses on the jаvascript version of LangChain. Save your time and learn up to 3X faster with a structured learning system that’s carefully crafted for beginners. LangChainJS For Beginners will help you harness the power of LangChain and jаvascript to develop AI-powered applications. In this book, I'll be using a step-by-step, practical approach so that you can build cutting-edge AI solutions using LangChain and jаvascript. By the end of the book, you will understand how to build a Next.js web application that harnesses the power of LLMs such as OpenAI's GPT and Google's Gemini. A Large Language Model (LLM for short) is a Machine Learning model that can understand and generate an output that humans can understand. LLMs are usually trained on a vast amount of text data available on the internet so that they can perform a wide range of language-related tasks such as translation, summarization, question answering, and creative writing. Examples of LLMs include GPT-4 by OpenAI, Gemini by Google, Llama by Meta, and Mistral by Mistral. Some LLMs are closed-source, like GPT and Gemini, while some are open-source such as Llama and Mistral. LangChain is an open-source framework designed to simplify the process of developing a LLM-powered application. LangChain enables you to integrate and call LLM which powers generative AI applications by simply calling the class that represents the model. Under the hood, LangChain will perform the steps required to interact with the language model API and manage the processing of input and output so that you can access different LLMs with minimal code change.

Название: Security for Cloud Native Applications: The practical guide for securing modern applications using AWS, Azure, and GCP
Автор: Eyal Estrin
Издательство: BPB Publications
Год: 2024
Страниц: 312
Язык: английский
Формат: pdf, epub (true)
Размер: 11.2 MB

Security for cloud-native applications is an overview of cloud-native application's characteristics from a security point of view, filled with best practices for securing services based on AWS, Azure, and GCP infrastructure. This book is a practical guide for securing cloud-native applications throughout their lifecycle. It establishes foundational knowledge of cloud services and cloud-native characteristics. It focuses on securing design approaches like APIs, microservices, and event-driven architectures. Specific technologies like containers, Kubernetes, and serverless functions are covered with security best practices. The book emphasizes integrating security throughout development using CI/CD pipelines and IaC tools. It explores policy as code for enforcing security policies and immutable infrastructure for enhanced security posture. Key management and threat detection strategies are also covered. Finally, the book offers a practical example and resources for further learning. Kubernetes is considered the de facto standard for Container orchestrators. It allows you to deploy applications on a large scale and spin up or down new containers, according to application load, ensuring all containers are healthy (otherwise, Kubernetes deploys new containers to replace the unhealthy ones). There are many benefits to choosing Kubernetes as an orchestrator for provisioning modern applications using containers. Kubernetes can be deployed and run almost anywhere, from managed cloud environments to on-prem clusters (local data centers) and at the edge where compute and storage resources are close to data generation. By the end of the book, the reader will be able to design and secure modern applications using the public cloud scale, managed services, automation, and built-in security controls.

Название: Percolation Theory Using Python
Автор: Anders Malthe-Sørenssen
Издательство: Springer
Год: 2024
Страниц: 221
Язык: английский
Формат: pdf (true), epub
Размер: 41.2 MB

This course-based textbook delves into percolation theory, examining the physical properties of random media—materials characterized by varying sizes of holes and pores. The focus is on both the mathematical foundations and the computational and statistical methods used in this field. Designed as a practical introduction, the book places particular emphasis on providing a comprehensive set of computational tools necessary for studying percolation theory. Readers will learn how to generate, analyze, and comprehend data and models, with detailed theoretical discussions complemented by accessible computer codes. The book's structure ensures a complete exploration of worked examples, encompassing theory, modeling, implementation, analysis, and the resulting connections between theory and analysis. Percolation is the study of connectivity of random media and of other properties of connected subsets of random media. In this book, we will address the physical properties of such media, develop the underlying mathematical theory and the computational and statistical methods needed to discuss the physical properties of random media. In order to do that, we will develop a simplified model system, a model porous medium, for which we can develop a well-founded mathematical theory, and then afterwards we can apply this model to realistic random systems. The basic terms in percolation theory are introduced, and you learn how to generate, visualize and measure on percolation systems in Python.

Название: Ultimate Azure Data Scientist Associate (DP-100) Certification Guide: Simplified Concepts and Effective ML Solutions to Crack the Azure Data Scientist DP-100 Exam
Автор: Rajib Kumar De
Издательство: Orange Education Pvt Ltd, AVA
Год: 2024
Страниц: 807
Язык: английский
Формат: pdf, epub
Размер: 25.6 MB

Empower Your Data Science Journey: From Exploration to Certification in Azure Machine Learning. Ultimate Azure Data Scientist Associate (DP-100) Certification Guide is your essential resource for achieving the Microsoft Azure Data Scientist Associate certification. This guide covers all exam objectives, helping you design and prepare machine learning solutions, explore data, train models, and manage deployment and retraining processes. The book starts with the basics and advances through hands-on exercises and real-world projects, to help you gain practical experience with Azure's tools and services. The book features certification-oriented Q&A challenges that mirror the actual exam, with detailed explanations to help you thoroughly grasp each topic. Perfect for aspiring data scientists, IT professionals, and analysts, this comprehensive guide equips you with the expertise to excel in the DP-100 exam and advance your Data Science career. In the fast-evolving landscape of Azure data science, embracing a framework that seamlessly blends power with elegance is paramount. Welcome to the modern cloud-based data science world — a journey that transcends the ordinary and propels you into the extraordinary. This book comprises 12 chapters, each a complete module in itself, serving as your comprehensive guide to mastering data science on Azure. It covers a wide array of topics, from the fundamentals to advanced techniques. Whether you are a seasoned developer looking to expand your skills or a newcomer eager to dive into Data Science, this book has something for everyone.